Evidence map›Paper›PMID 39190910›Full record

SynthesisJournal of medical Internet research2024

Framework Development for Reducing Attrition in Digital Dietary Interventions: Systematic Review and Thematic Synthesis.

Jian Wang, Jinli Mahe, Yujia Huo, Weiyuan Huang, Xinru Liu, Yang Zhao, Junjie Huang, Feng Shi, Zhihui Li, Dou Jiang and 4 more

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Jian WangThe School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.ORCID 0000-0001-9739-3434
Jinli MaheThe School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.ORCID 0009-0000-0235-9461
Yujia HuoThe School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.ORCID 0009-0000-5074-1729
Weiyuan HuangThe School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.ORCID 0009-0005-9314-8665
Xinru LiuThe School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.ORCID 0009-0007-9237-5211
Yang ZhaoThe George Institute for Global Health, University of New South Wales, Sydney, Australia.ORCID 0000-0002-6011-5948
Junjie HuangThe Jockey Club School of Public Health and Primary Care, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong, China (Hong Kong).ORCID 0000-0003-2382-4443
Feng ShiEast China Aviation Personnel Medical Appraisal Center, Shanghai, China.ORCID 0009-0000-6914-0827
Zhihui LiTsinghua Vanke School of Public Health, Tsinghua University, Shenzhen, China.ORCID 0000-0001-5356-932X
Dou JiangSchool of Economics and Management, Southeast University, Nanjing, China.ORCID 0009-0000-6229-1534
Yilong LiSchool of Economics and Management, Southeast University, Nanjing, China.ORCID 0009-0007-5693-627X
Garon PercevalSuzhou Industrial Park Monash Research Institute of Science and Technology, Monash University, Suzhou, China.ORCID 0000-0003-2352-108X
Lindu ZhaoSchool of Economics and Management, Southeast University, Nanjing, China.ORCID 0000-0003-4902-3679
Lin ZhangThe School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.ORCID 0000-0002-2064-8440

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDietary behaviors significantly influence health outcomes across populations. Unhealthy diets are linked to serious diseases and substantial economic burdens, contributing to approximately 11 million deaths and significant disability-adjusted life years annually. Digital dietary interventions offer accessible solutions to improve dietary behaviors. However, attrition, defined as participant dropout before intervention completion, is a major challenge, with rates as high as 75%-99%. High attrition compromises intervention validity and reliability and exacerbates health disparities, highlighting the need to understand and address its causes.

objectiveThis study systematically reviews the literature on attrition in digital dietary interventions to identify the underlying causes, propose potential solutions, and integrate these findings with behavior theory concepts to develop a comprehensive theoretical framework. This framework aims to elucidate the behavioral mechanisms behind attrition and guide the design and implementation of more effective digital dietary interventions, ultimately reducing attrition rates and mitigating health inequalities.

methodsWe conducted a systematic review, meta-analysis, and thematic synthesis. A comprehensive search across 7 electronic databases (PubMed, MEDLINE, Embase, CENTRAL, Web of Science, CINAHL Plus, and Academic Search Complete) was performed for studies published between 2013 and 2023. Eligibility criteria included original research exploring attrition in digital dietary interventions. Data extraction focused on study characteristics, sample demographics, attrition rates, reasons for attrition, and potential solutions. We followed ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and used RStudio (Posit) for meta-analysis and NVivo for thematic synthesis.

resultsOut of the 442 identified studies, 21 met the inclusion criteria. The meta-analysis showed mean attrition rates of 35% for control groups, 38% for intervention groups, and 40% for observational studies, with high heterogeneity (I²=94%-99%) indicating diverse influencing factors. Thematic synthesis identified 15 interconnected themes that align with behavior theory concepts. Based on these themes, the force-resource model was developed to explore the underlying causes of attrition and guide the design and implementation of future interventions from a behavior theory perspective.

conclusionsHigh attrition rates are a significant issue in digital dietary interventions. The developed framework conceptualizes attrition through the interaction between the driving force system and the supporting resource system, providing a nuanced understanding of participant attrition, summarized as insufficient motivation and inadequate or poorly matched resources. It underscores the critical necessity for digital dietary interventions to balance motivational components with available resources dynamically. Key recommendations include user-friendly design, behavior-factor activation, literacy training, force-resource matching, social support, personalized adaptation, and dynamic follow-up. Expanding these strategies to a population level can enhance digital health equity. Further empirical validation of the framework is necessary, alongside the development of behavior theory-guided guidelines for digital dietary interventions.

trial registrationPROSPERO CRD42024512902; https://tinyurl.com/3rjt2df9.

Indexed as

Diet TherapyHumansPatient Dropoutsattrition ratebehavior change theorydigital dietary interventiondigital healthdropouteHealthemailmHealthmobile appsthematic synthesis

Identifiers

PMID39190910
PMCPMC11387916

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.